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Table Of Contents

Mastering Gephi Network Visualization

4.6 (8)

Mastering Gephi Network Visualization

4.6 (8)

Overview of this book

This book is intended for anyone interested in advanced network analysis. If you wish to master the skills of analyzing and presenting network graphs effectively, then this is the book for you. No coding experience is required to use this book, although some familiarity with the Gephi user interface will be helpful.

Preface

Preface

What this book covers

What you need for this book

Who this book is for

Conventions

Reader feedback

Customer support

Free Chapter

1. Fundamentals of Complex Networks and Gephi

1. Fundamentals of Complex Networks and Gephi

Graph applications

A network graph analysis primer

Overviewing Gephi

Primary windows

Secondary windows – tabs

Essential plugins

Summary

2. A Network Graph Framework

2. A Network Graph Framework

A proposed process flow

Creating an example graph

Analyzing the graph

Modifying the graph

Exporting the graph

Summary

3. Selecting the Layout

3. Selecting the Layout

Overviewing the layout types

Assessing your graphing needs

Layout strengths and weaknesses

Testing layouts

Layout selection criteria

Graph aesthetics

Summary

4. Network Patterns

4. Network Patterns

Contagion and diffusion

Clustering and homophily

Network growth patterns

Using Gephi generators

Viewing a contagion network

Viewing network diffusion

Network clustering

Identifying homophily

Summary

5. Working with Filters

5. Working with Filters

The filtering theory

Primary filtering functions in Gephi

Using simple filters

Working with complex filters

Summary

6. Graph Statistics

6. Graph Statistics

Overview of graph statistics

Interpreting graph statistics

Application of statistical measures

Summary

7. Segmenting and Partitioning a Graph

7. Segmenting and Partitioning a Graph

Partitioning and clustering options

Partitioning and clustering examples

Summary

8. Dynamic Networks

8. Dynamic Networks

When to use DNA

Topology-based DNA

Attribute-based DNA

Creating dynamic GEXF files

Summary

9. Taking Your Graph Beyond Gephi

9. Taking Your Graph Beyond Gephi

Overview of the available tools

Exporting a web graph

Summary

10. Putting It All Together

10. Putting It All Together

Using Gephi to understand existing networks

Creating new Gephi projects

Anticipating the future of network analysis

Summary

A. Data Sources and Other Web Resources

A. Data Sources and Other Web Resources

Data sources

Web resources

Import processes

Bibliography

Index

Index

Contagion and diffusion

Contagion and diffusion are related concepts that are often best understood through network analysis. The use of network graphs can help you provide considerable insight into the potential spread of a disease as well as the success of a new innovation. This is done by exposing the structure of the underlying network. Densely connected networks can be effective in both of these realms, which can have both positive and negative effects, depending on whether we are viewing the diffusion of a positive innovation, or conversely, the spread of an infectious disease.

Contagion

One of the most intriguing and potentially valuable ways of using networks is to examine how disease transmission works within a network, and how the structure of a network can either promote or limit the spread of the disease. If the transmission pattern can be altered through some sort of intervention, such as vaccination or even simple avoidance (for example, not contacting a friend if there is a...

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